5 leading data archiving solutions for secure storage

Every production database accumulates records that your data engineering team rarely queries but can’t delete. Regulatory retention policies, audit requirements, and historical reporting needs force organizations to keep years of data available.

The right data archiving solution reduces storage costs and protects query performance while keeping records accessible when compliance or analytics require them. Here’s a breakdown of five archiving platforms and the criteria that matter most when choosing the right fit.

What is a data archiving solution?

A data archive solution is a platform that relocates aging, low-traffic records away from live databases into dedicated retention storage. The goal is to reduce compute and storage spend on production systems while keeping older records intact and indexed for compliance or analysis.

Archiving platforms compress, index, and secure records so they remain searchable and recoverable even after years in storage. Unlike a standard backup, which duplicates the full production environment for disaster recovery, an archive selectively relocates individual records into lower-cost storage where they stay accessible for compliance and analysis.

The typical archiving workflow starts with a policy engine that flags records based on age, last access date, or regulatory category. Once flagged, those records get compressed and written to a lower-cost storage tier, with their associated tags and metadata preserved. This allows compliance or analytics teams to search and retrieve exactly what they need without restoring entire data sets.

Organizations in healthcare, financial services, and government rely on archiving to fulfill regulatory mandates while keeping their production databases lean. Common mandates include the Health Insurance Portability and Accountability Act (HIPAA), the General Data Protection Regulation (GDPR), the Sarbanes-Oxley Act (SOX), and the Financial Industry Regulatory Authority (FINRA) record-keeping rules.

Types of data archiving solutions

Data archiving platforms fall into four common categories, each suited to a different infrastructure setup and compliance profile:

• Cloud-based archiving: Cloud archiving solutions store archived records in cloud object storage, such as Amazon S3, Azure Blob, and Google Cloud Storage, with pay-as-you-go pricing. This model suits organizations that want flexible storage without managing physical hardware.
• On-premises archiving: On-premises platforms keep archived data on local servers or network-attached storage. Local retention suits organizations with strict data sovereignty requirements or air-gapped security mandates.
• Hybrid archiving: A hybrid model splits archived data between on-premises and cloud storage. Sensitive records stay local, while less regulated data moves to lower-cost cloud tiers.
• Application-specific archiving: Single-system archiving targets data from one application, like email (Exchange, Gmail), a CRM (Salesforce), or an ERP (SAP). The scope is narrower, focused on retention and electronic discovery (eDiscovery) for one platform rather than the full enterprise data estate.

Your choice depends on regulatory exposure, data volume, and how often you need to retrieve archived records.

Top 5 data archiving solutions

These five data archiving platforms handle different archiving needs, from retaining structured enterprise data at scale to capturing regulated communications for compliance.

1. Archon Data Store

Best for: Enterprise-wide archiving across structured data, ERP systems, HR platforms, and unstructured content

Key feature: Archon’s Lakehouse architecture stores both structured and unstructured data in one governed environment using open formats, so your team can query archived records with standard SQL.

Archon Data Store is an enterprise archiving solution built for multi-system data estates. The platform connects to more than 250 enterprise systems — including SAP, Oracle, and PeopleSoft — through open APIs and native ETL connectors. Archon tags every record with metadata at ingestion, applies automated retention policies, and stores data in tiered storage with up to 80% compression. The platform also includes a logically air-gapped Data Bunker that isolates sensitive records from network-accessible environments.

2. Arctera (formerly Veritas)

Best for: Teams looking to archive email and file server data at scale, especially in finance, healthcare, and legal sectors

Key feature: Enterprise Vault archives over 120 content sources, such as email, Teams, SharePoint, file servers, and social media, into a single repository with unified eDiscovery search across all archived content types.

Arctera Enterprise Vault, formerly Veritas Enterprise Vault, has been in production for more than two decades, making it one of the longest-running data archiving solutions on the market. The platform automates retention management, data classification, and supervision across unstructured content. Its Compliance Accelerator and Discovery Accelerator modules support legal hold workflows for regulated industries.

3. Smarsh

Best for: Financial services firms that must archive digital communications to meet FINRA, Securities and Exchange Commission (SEC), and global record-keeping requirements.

Key feature: Smarsh captures data from more than 80 communication channels and uses AI-powered supervision to flag policy violations before they become regulatory issues.

Smarsh is a communications compliance platform trusted by over 6,500 customers globally. Its archive stores data in immutable, write-once, read-many storage for SEC 17a-4 compliance, supports configurable legal holds, and provides defensible deletion workflows. The platform is purpose-built for regulated industries where communications must be retained, supervised, and produced on demand for regulators or litigation.

4. Microsoft Purview

Best for: Organizations already using Microsoft 365 E3 or E5 that want archiving, data lifecycle management, and governance controls in one platform

Key feature: Purview applies retention labels and eDiscovery holds to archived content natively within the Microsoft 365 environment, removing the need for a separate archiving vendor.

Microsoft Purview unifies data governance, compliance, and risk management across Microsoft 365, Azure, and multi-cloud environments such as AWS and Google Cloud. Its Data Lifecycle Management module lets administrators set retention and deletion policies that automatically move aging content into archive mailboxes or archived SharePoint tiers. Purview’s strength is its native integration with the Microsoft ecosystem.

5. Archive360

Best for: Teams migrating legacy archives (on-premises email, file shares, and database backups) to cloud storage while maintaining chain of custody for compliance

Key feature: Archive360’s FastCollect engine moves data from legacy archiving systems up to 20 times faster than API-based migration tools while preserving full audit trails.

Archive360 runs on a cloud-native platform inside your own Azure tenant, so archived data stays inside your environment in its native format. The platform supports compliance archiving, data retention, advanced search, legal holds, and defensible deletion across both structured and unstructured data. Archive360 is a strong fit for organizations that need to decommission aging on-premises archives and consolidate records into modern cloud storage without losing audit trails or legal defensibility.

How to choose a data archiving solution

Selecting the right long-term data archiving solution depends on key factors that vary by industry, infrastructure, and regulatory exposure:

• Regulatory coverage: Make sure the platform supports your specific mandates, whether it’s SEC 17a-4 WORM immutability for financial services or HIPAA audit logging for healthcare.
• Total cost of ownership: Compare per-GB, per-user, and tiered-storage pricing against your projected data growth, and check whether the platform automatically compresses and deduplicates archived records.
• Retrieval speed and analytical query support: Determine whether your team needs sub-second eDiscovery search or can work with batch retrieval, especially if analysts plan to run SQL queries against archived data.
• Compatibility with your data infrastructure: Confirm the platform connects to both the sources you archive and the destinations your team queries, so your data engineering team doesn’t have to build custom export pipelines.

Regulatory coverage matters most for compliance and legal teams, while data engineering and analytics teams focus more on retrieval speed and infrastructure compatibility.

How a Fivetran data lake complements archiving

Automated data integration and data archiving solve parallel problems. Archiving platforms move old records into cold storage under the assumption that they’re not actively needed for analysis, which means they can’t be directly queried for analytics and AI workloads.

By contrast, a data lake with the right architecture is purpose-built to support analytics and AI. Fivetran’s Managed Data Lake Service moves data from more than 750 sources into open table formats in your own cloud storage. When a source adds or renames a field, Fivetran updates the destination tables automatically.

The platform handles ongoing table compaction and deduplication, and its extensibility and management APIs give your data engineering team programmatic control over sync scheduling.

Start a free trial to see how Fivetran works with your data.

FAQ

What are the benefits of using an archiving application?

An archiving application reduces production database size by moving aged records to lower-cost storage, which improves query performance for your analytics engineers and lowers compute costs on your primary warehouse. Archiving also enforces automated retention and deletion schedules to meet regulatory mandates like GDPR and SOX without requiring manual record management by your compliance team.

What mistakes should businesses avoid when implementing a data archiving solution?

The most common mistake is archiving data without defining retention policies first, which results in records that either get deleted too early or accumulate indefinitely without governance. Another common error is choosing a platform that locks archived records in proprietary formats, which forces your data engineering team to build custom extraction pipelines when a different department needs access to historical data.

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